- 500,000 participants
- 100,000 inlucded in the sub-study
- Can infer movement with longitudinal follow-up
| Completed: good data | Completed: bad data | No response | Not asked | |
|---|---|---|---|---|
| n | 96701 | 7005 | 132800 | 266110 |
| Age at Initial Visit (mean (sd)) | 56.6 (7.8) | 55.2 (7.9) | 56.4 (8.0) | 57.5 (8.1) |
| Male (% Male) | 42255 (43.7) | 3156 (45.1) | 62601 (47.1) | 121151 (45.5) |
| Ethnicity (% Non-White) | 2983 (3.1) | 335 (4.8) | 7617 (5.8) | 16102 (6.1) |
Many people DIED before being able to be asked
| Completed: good data | Completed: bad data | No response | Not asked | |
|---|---|---|---|---|
| Overall health (%) | ||||
| Excellent | 20987 (21.8) | 1464 (21.0) | 21583 (16.3) | 37849 (14.4) |
| Good | 57849 (60.0) | 4057 (58.1) | 78968 (59.7) | 148196 (56.2) |
| Fair | 15149 (15.7) | 1261 (18.0) | 26669 (20.2) | 62313 (23.6) |
| Poor | 2482 (2.6) | 205 (2.9) | 4969 (3.8) | 15124 (5.7) |
Auto-calibration [@van2014autocalibration]
@doherty2017large
“We removed non-wear time, defined as consecutive stationary episodes lasting for at least 60 minutes where all three axes had a standard deviation of less than 13.0 m\(g\)”
@doherty2017large
“Here, 13 m\(g\) was selected just above the empirically derived baseline (noise) standard deviation of 10 m\(g\) to retain only nonmovement periods.” @van2014autocalibration
“We invited some participants to wear an activity monitor for a week, four times a year. … finished in early 2019.”